Accuracy assessment of fusion transcript detection via read-mapping and de novo fusion transcript assembly-based methods
Open accessAbstract
BACKGROUND: Accurate fusion transcript detection is essential for comprehensive characterization of cancer transcriptomes. Over the last decade, multiple bioinformatic tools have been developed to predict fusions from RNA-seq, based on either read mapping or de novo fusion transcript assembly. RESULTS: We benchmark 23 different methods including applications we develop, STAR-Fusion and TrinityFusion, leveraging both simulated and real RNA-seq. Overall, STAR-Fusion, Arriba, and STAR-SEQR are the most accurate and fastest for fusion detection on cancer transcriptomes. CONCLUSION: The lower accuracy of de novo assembly-based methods notwithstanding, they are useful for reconstructing fusion isoforms and tumor viruses, both of which are important in cancer research.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
Fast and accurate short read alignment with Burrows-Wheeler transform
Li, H., & Durbin, R. (2009) · Bioinformatics · doi:10.1093/bioinformatics/btp324 · Cited by 58,607 · see citing works
Fast gapped-read alignment with Bowtie 2
Langmead, B., & Salzberg, S. L. (2012) · Nature Methods · doi:10.1038/nmeth.1923 · Cited by 56,400 · see citing works
STAR: ultrafast universal RNA-seq aligner
Dobin, A., Davis, C. A., Schlesinger, F., Drenkow, J., Zaleski, C., Jha, S., Batut, P., Chaisson, M., & Gingeras, T. R. (2013) · Bioinformatics · doi:10.1093/bioinformatics/bts635 · Cited by 51,709 · see citing works
Self-citationRSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome
Li, B., & Dewey, C. N. (2011) · BMC Bioinformatics · doi:10.1186/1471-2105-12-323 · Cited by 22,179 · see citing works
Self-citationBLAST+: architecture and applications
Camacho, C., Coulouris, G., Avagyan, V., Ma, N., Papadopoulos, J., Bealer, K., & Madden, T. L. (2009) · BMC Bioinformatics · doi:10.1186/1471-2105-10-421 · Cited by 22,074 · see citing works
Ultrafast and memory-efficient alignment of short DNA sequences to the human genome.
Langmead, B., Trapnell, C., Pop, M., & Salzberg, S. L. (2009) · Genome Biology · doi:10.1186/gb-2009-10-3-r25 · Cited by 21,849 · see citing works
Full-length transcriptome assembly from RNA-Seq data without a reference genome
Grabherr, M. G., Haas, B. J., Yassour, M., Levin, J. Z., Thompson, D. A., Amit, I., Adiconis, X., Fan, L., Raychowdhury, R., Zeng, Q., et al. (2011) · Nature Biotechnology · doi:10.1038/nbt.1883 · Cited by 20,776 · see citing works
Self-citationKim, D., Pertea, G., Trapnell, C., Pimentel, H., Kelley, R., & Salzberg, S. L. (2013) · Genome Biology · doi:10.1186/gb-2013-14-4-r36 · Cited by 12,668 · see citing works
TopHat: discovering splice junctions with RNA-Seq
Trapnell, C., Pachter, L. S., & Salzberg, S. L. (2009) · Bioinformatics · doi:10.1093/bioinformatics/btp120 · Cited by 11,477 · see citing works
Near-optimal probabilistic RNA-seq quantification
Bray, N. L., Pimentel, H., Melsted, P., & Pachter, L. (2016) · Nature Biotechnology · doi:10.1038/nbt.3519 · Cited by 9,723 · see citing works
<tt>BLAT</tt> —The <tt>BLAST</tt> -Like Alignment Tool
Kent, W. J. (2002) · Genome Research · doi:10.1101/gr.229202 · Cited by 8,480 · see citing works
Haas, B. J., Papanicolaou, A., Yassour, M., Grabherr, M., Blood, P. D., Bowden, J., Couger, M. B., Eccles, D., Li, B., Lieber, M., et al. (2013) · Nature Protocols · doi:10.1038/nprot.2013.084 · Cited by 8,464 · see citing works
Self-citationThe Cancer Cell Line Encyclopedia enables predictive modelling of anticancer drug sensitivity
Barretina, J., Caponigro, G., Stransky, N., Venkatesan, K., Margolin, A. A., Kim, S., Wilson, C. J., Lehár, J., Kryukov, G. V., Sonkin, D., et al. (2012) · Nature · doi:10.1038/nature11003 · Cited by 7,950 · see citing works
Self-citationThe relationship between Precision-Recall and ROC curves
Davis, J., & Goadrich, M. (2006) · Proceedings of the 23rd international conference on Machine learning - ICML '06 · doi:10.1145/1143844.1143874 · Cited by 6,559 · see citing works
Recurrent Fusion of <i>TMPRSS2</i> and ETS Transcription Factor Genes in Prostate Cancer
Tomlins, S. A., Rhodes, D. R., Perner, S., Dhanasekaran, S. M., Mehra, R., Sun, X.-W., Varambally, S., Cao, X., Tchinda, J., Kuefer, R., et al. (2005) · Science · doi:10.1126/science.1117679 · Cited by 3,846 · see citing works
UpSetR: an R package for the visualization of intersecting sets and their properties
Conway, J. R., Lex, A., & Gehlenborg, N. (2017) · Bioinformatics · doi:10.1093/bioinformatics/btx364 · Cited by 3,586 · see citing works
Five-Year Follow-up of Patients Receiving Imatinib for Chronic Myeloid Leukemia
Druker, B. J., Guilhot, F., O’Brien, S. G., Gathmann, I., Kantarjian, H. M., Gattermann, N., Deininger, M. W., Silver, R. T., Goldman, J. M., Stone, R. M., et al. (2006) · New England Journal of Medicine · doi:10.1056/nejmoa062867 · Cited by 3,473 · see citing works
(2004) · Choice Reviews Online · doi:10.5860/choice.42-1645 · Cited by 2,928 · see citing works
Proceedings of the 23rd international conference on Machine learning
Cohen, W. W., & Moore, A. (2006) · Cited by 2,647 · see citing works
GMAP: A genomic mapping and alignment program for mRNA and EST sequences
Wu, T. D., & Watanabe, C. K. (2005) · Bioinformatics · doi:10.1093/bioinformatics/bti310 · Cited by 2,354 · see citing works
Crizotinib in <i>ROS1</i>-Rearranged Non–Small-Cell Lung Cancer
Shaw, A. T., Ou, S.-H. I., Bang, Y.-J., Camidge, D. R., Solomon, B. J., Salgia, R., Riely, G. J., Varella-Garcia, M., Shapiro, G. I., Costa, D. B., et al. (2014) · New England Journal of Medicine · doi:10.1056/nejmoa1406766 · Cited by 1,964 · see citing works
COSMIC: somatic cancer genetics at high-resolution
Forbes, S. A., Beare, D., Boutselakis, H., Bamford, S., Bindal, N., Tate, J., Cole, C. G., Ward, S., Dawson, E., Ponting, L., et al. (2017) · Nucleic Acids Research · doi:10.1093/nar/gkw1121 · Cited by 1,922 · see citing works
Centrifuge: rapid and sensitive classification of metagenomic sequences
Kim, D., Song, L., Breitwieser, F. P., & Salzberg, S. L. (2016) · Genome Research · doi:10.1101/gr.210641.116 · Cited by 1,438 · see citing works
Oases:robustde novoRNA-seq assembly across the dynamic range of expression levels
Schulz, M. H., Zerbino, D. R., Vingron, M., & Birney, E. (2012) · Bioinformatics · doi:10.1093/bioinformatics/bts094 · Cited by 1,423 · see citing works
Garrett, W. S. (2015) · Science · doi:10.1126/science.aaa4972 · Cited by 1,404 · see citing works
Mapping RNA‐seq Reads with STAR
Dobin, A., & Gingeras, T. (2015) · Current Protocols in Bioinformatics · doi:10.1002/0471250953.bi1114s51 · Cited by 1,265 · see citing works
Self-citationMapSplice: Accurate mapping of RNA-seq reads for splice junction discovery
Wang, K., Singh, D., Zeng, Z., Coleman, S. J., Huang, Y., Savich, G. L., He, X., Mieczkowski, P., Grimm, S. A., Perou, C. M., et al. (2010) · Nucleic Acids Research · doi:10.1093/nar/gkq622 · Cited by 1,193 · see citing works
The landscape of kinase fusions in cancer
Stransky, N., Cerami, E., Schalm, S., Kim, J. L., & Lengauer, C. (2014) · Nature Communications · doi:10.1038/ncomms5846 · Cited by 968 · see citing works
Self-citationTopHat-Fusion: an algorithm for discovery of novel fusion transcripts
Kim, D., & Salzberg, S. L. (2011) · Genome biology · doi:10.1186/gb-2011-12-8-r72 · Cited by 806 · see citing works
A comprehensive transcriptional portrait of human cancer cell lines
Klijn, C. N., Durinck, S., Stawiski, E. W., Haverty, P. M., Jiang, Z., Liu, H., Degenhardt, J. D., Mayba, O., Gnad, F., Liu, J., et al. (2014) · Nature Biotechnology · doi:10.1038/nbt.3080 · Cited by 650 · see citing works
Driver Fusions and Their Implications in the Development and Treatment of Human Cancers
Gao, Q., Liang, W.-W., Foltz, S. M., Mutharasu, G., Jayasinghe, R. G., Cao, S., Liao, W., Reynolds, S. M., Wyczalkowski, M. A., Yao, L., et al. (2018) · Cell Reports · doi:10.1016/j.celrep.2018.03.050 · Cited by 597 · see citing works
deFuse: An Algorithm for Gene Fusion Discovery in Tumor RNA-Seq Data
McPherson, A., Hormozdiari, F., Zayed, A., Giuliany, R., Ha, G., Sun, M. G. F., Griffith, M., Heravi Moussavi, A., Senz, J., Melnyk, N., et al. (2011) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1001138 · Cited by 557 · see citing works
The GEM mapper: fast, accurate and versatile alignment by filtration
Marco‐Sola, S., Sammeth, M., Guigó, R., & Ribeca, P. (2012) · Nature Methods · doi:10.1038/nmeth.2221 · Cited by 523 · see citing works
Detection of a Recurrent DNAJB1-PRKACA Chimeric Transcript in Fibrolamellar Hepatocellular Carcinoma
Honeyman, J. N., Simon, E. P., Robine, N., Chiaroni-Clarke, R. C., Darcy, D. G., Lim, I. I. P., Gleason, C. E., Murphy, J. M., Rosenberg, B. R., Teegan, L., et al. (2014) · Science · doi:10.1126/science.1249484 · Cited by 491 · see citing works
The landscape and therapeutic relevance of cancer-associated transcript fusions
Yoshihara, K., Wang, Q., Torres-Garcia, W., Zheng, S., Vegesna, R., Kim, H., & Verhaak, R. G. W. (2015) · Oncogene · doi:10.1038/onc.2014.406 · Cited by 450 · see citing works
Targeting cancer with kinase inhibitors
Gross, S. D., Rahal, R., Stransky, N., Lengauer, C., & Hoeflich, K. P. (2015) · Journal of Clinical Investigation · doi:10.1172/jci76094 · Cited by 442 · see citing works
Self-citationGMAP and GSNAP for Genomic Sequence Alignment: Enhancements to Speed, Accuracy, and Functionality
Wu, T. D., Reeder, J., Lawrence, M. F., Becker, G., & Brauer, M. J. (2016) · Methods in molecular biology · doi:10.1007/978-1-4939-3578-9_15 · Cited by 419 · see citing works
FusionCatcher – a tool for finding somatic fusion genes in paired-end RNA-sequencing dataPreprint
Nicorici, D., Şatalan, M., Edgren, H., Kangaspeska, S., Murumägi, A., Kallioniemi, O., Virtanen, S. M. M., & Kilkku, O. (2014) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/011650 · Cited by 392 · see citing works
Chimeric transcript discovery by paired-end transcriptome sequencing
Maher, C. A., Palanisamy, N., Brenner, J. C., Cao, X., Kalyana-Sundaram, S., Luo, S., Khrebtukova, I., Barrette, T. R., Grasso, C., Yu, J., et al. (2009) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0904720106 · Cited by 339 · see citing works
Identification of fusion genes in breast cancer by paired-end RNA-sequencing
Edgren, H., Murumägi, A., Kangaspeska, S., Nicorici, D., Hongisto, V., Sahlberg, K. K., Rye, I. H., Nyberg, S., Wolf, M., Børresen‐Dale, A., et al. (2011) · Genome biology · doi:10.1186/gb-2011-12-1-r6 · Cited by 313 · see citing works
ChimeraScan: a tool for identifying chimeric transcription in sequencing data
Iyer, M. K., Chinnaiyan, A. M., & Maher, C. A. (2011) · Bioinformatics · doi:10.1093/bioinformatics/btr467 · Cited by 277 · see citing works
Optimizing RNA-Seq Mapping with STAR
Dobin, A., & Gingeras, T. (2016) · Methods in molecular biology · doi:10.1007/978-1-4939-3572-7_13 · Cited by 250 · see citing works
Self-citationTumorFusions: an integrative resource for cancer-associated transcript fusions
Hu, X., Wang, Q., Tang, M., Barthel, F. P., Amin, S. B., Yoshihara, K., Lang, F., Martínez-Ledesma, E., Lee, S. H., Zheng, S., et al. (2017) · Nucleic Acids Research · doi:10.1093/nar/gkx1018 · Cited by 239 · see citing works
Haas, B. J., & Zody, M. C. (2010) · Nature Biotechnology · doi:10.1038/nbt0510-421 · Cited by 237 · see citing works
Self-citationDiscovering chimeric transcripts in paired-end RNA-seq data by using EricScript
Benelli, M., Pescucci, C., Marseglia, G., Severgnini, M., Torricelli, F., & Magi, A. (2012) · Bioinformatics · doi:10.1093/bioinformatics/bts617 · Cited by 220 · see citing works
SOAPfuse: an algorithm for identifying fusion transcripts from paired-end RNA-Seq data
Jia, W., Qiu, K., He, M., Song, P., Zhou, Q., Zhou, F., Yu, Y., Zhu, D., Nickerson, M. L., Wan, S., et al. (2013) · Genome biology · doi:10.1186/gb-2013-14-2-r12 · Cited by 206 · see citing works
Recurrent chimeric fusion RNAs in non-cancer tissues and cells
Babiceanu, M., Qin, F., Xie, Z., Jia, Y., Lopez, K., Janus, N., Facemire, L., Kumar, S., Pang, Y., Qi, Y., et al. (2016) · Nucleic Acids Research · doi:10.1093/nar/gkw032 · Cited by 202 · see citing works
Discovering and understanding oncogenic gene fusions through data intensive computational approaches
Latysheva, N. S., & Babu, M. M. (2016) · Nucleic Acids Research · doi:10.1093/nar/gkw282 · Cited by 194 · see citing works
JAFFA: High sensitivity transcriptome-focused fusion gene detection
Davidson, N., Majewski, I. J., & Oshlack, A. (2015) · Genome Medicine · doi:10.1186/s13073-015-0167-x · Cited by 173 · see citing works
PRADA: pipeline for RNA sequencing data analysis
Torres‐García, W., Zheng, S., Sivachenko, A., Vegesna, R., Wang, Q., Yao, R., Berger, M. F., Weinstein, J. N., Getz, G. A., & Verhaak, R. G. W. (2014) · Bioinformatics · doi:10.1093/bioinformatics/btu169 · Cited by 154 · see citing works
Comparative assessment of methods for the fusion transcripts detection from RNA-Seq data
Kumar, S., Vo, A. D., Qin, F., & Li, H. (2016) · Scientific Reports · doi:10.1038/srep21597 · Cited by 153 · see citing works
Wang, Q., Xia, J., Jia, P., Pao, W. J., & Zhao, Z. (2012) · Briefings in Bioinformatics · doi:10.1093/bib/bbs044 · Cited by 119 · see citing works
Asmann, Y. W., Hossain, A., Necela, B. M., Middha, S., Kalari, K. R., Sun, Z., Chai, H. S., Williamson, D. W., Radisky, D. C., Schroth, G. P., et al. (2011) · Nucleic Acids Research · doi:10.1093/nar/gkr362 · Cited by 114 · see citing works
Crizotinib in ROS1-Rearranged Non–Small-Cell Lung Cancer
Shaw, A. T., & Solomon, B. J. (2015) · New England Journal of Medicine · doi:10.1056/nejmc1415359 · Cited by 112 · see citing works
Oncogenic Role of Tumor Viruses in Humans
Akram, N., Imran, M., Noreen, M., Ahmed, F., Atif, M., Fatima, Z., & Waqar, A. B. (2016) · Viral Immunology · doi:10.1089/vim.2016.0109 · Cited by 101 · see citing works
State-of-the-Art Fusion-Finder Algorithms Sensitivity and Specificity
Carrara, M., Beccuti, M., Lazzarato, F., Cavallo, F., Cordero, F., Donatelli, S., & Calogero, R. (2013) · BioMed Research International · doi:10.1155/2013/340620 · Cited by 94 · see citing works
FusionHunter: identifying fusion transcripts in cancer using paired-end RNA-seq
Li, Y., CHIEN, J. R., Smith, D. I., & Ma, J. (2011) · Bioinformatics · doi:10.1093/bioinformatics/btr265 · Cited by 87 · see citing works
Reanalysis of RNA-Sequencing Data Reveals Several Additional Fusion Genes with Multiple Isoforms
Kangaspeska, S., Hultsch, S., Edgren, H., Nicorici, D., Murumägi, A., & Kallioniemi, O. (2012) · PLoS ONE · doi:10.1371/journal.pone.0048745 · Cited by 85 · see citing works
ChimerDB 2.0—a knowledgebase for fusion genes updated
Kim, P., Yoon, S., Kim, N., Lee, S., Ko, M., Lee, H., Kang, H., Kim, J., & Lee, S. (2009) · Nucleic Acids Research · doi:10.1093/nar/gkp982 · Cited by 78 · see citing works
nFuse: Discovery of complex genomic rearrangements in cancer using high-throughput sequencingPreprint
McPherson, A., Wu, C., Wyatt, A. W., Shah, S. P., Collins, C. C., & Şahinalp, S. C. (2012) · Genome Research · doi:10.1101/gr.136572.111 · Cited by 72 · see citing works
InFusion: Advancing Discovery of Fusion Genes and Chimeric Transcripts from Deep RNA-Sequencing Data
Okonechnikov, K., Imai‐Matsushima, A., Paul, L., Seitz, A., Meyer, T. F., & García-Alcalde, F. (2016) · PLoS ONE · doi:10.1371/journal.pone.0167417 · Cited by 60 · see citing works
Anaplastic lymphoma kinase: Role in cancer and therapy perspective
Zhao, Z., Verma, V., & Zhang, M. (2015) · Cancer Biology & Therapy · doi:10.1080/15384047.2015.1095407 · Cited by 50 · see citing works
Alaei-Mahabadi, B., Bhadury, J., Karlsson, J. W., Nilsson, J. A., & Larsson, E. (2016) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1606220113 · Cited by 50 · see citing works
Sfanos, K. S., Aloia, A. L., Hicks, J. L., et al. (2011) · PLoS ONE · doi:10.1371/journal.pone.0020874 · Cited by 49 · see citing works
Oda, T., Ikeda, S., Watanabe, S., Hatsushika, M., Akiyama, K., & Mitsunobu, F. (1988) · Virology · doi:10.1016/0042-6822(88)90109-2 · Cited by 46 · see citing works
Fusion detection and quantification by pseudoalignmentPreprint
Melsted, P., Hateley, S. L., Joseph, I., Pimentel, H., Bray, N., & Pachter, L. S. (2017) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/166322 · Cited by 45 · see citing works
Greger, L., Su, J., Rung, J., Ferreira, P. G., Lappalainen, T., Dermitzakis, E. T., & Brāzma, A. (2014) · PLoS ONE · doi:10.1371/journal.pone.0104567 · Cited by 37 · see citing works
ChimPipe: accurate detection of fusion genes and transcription-induced chimeras from RNA-seq data
Rodríguez–Martín, B., Palumbo, E., Marco‐Sola, S., Griebel, T., Ribeca, P., Alonso, G., Rastrojo, A., Aguado, B., Guigó, R., & Djebali, S. (2017) · BMC Genomics · doi:10.1186/s12864-016-3404-9 · Cited by 33 · see citing works
STAR Chimeric Post for rapid detection of circular RNA and fusion transcripts
Akers, N. K., Schadt, E. E., & Losic, B. (2018) · Bioinformatics · doi:10.1093/bioinformatics/bty091 · Cited by 28 · see citing works
Lim, T., Sl, T., Lim, P. S., et al. (2005) · Annals of the Academy of Medicine Singapore · doi:10.47102/annals-acadmedsg.v34n9p533 · Cited by 25 · see citing works
Short Read Alignment Using SOAP2
Hurgobin, B. (2015) · Methods in molecular biology · doi:10.1007/978-1-4939-3167-5_13 · Cited by 21 · see citing works
PO-400 Arriba – fast and accurate gene fusion detection from RNA-seq data
Uhrig, S., Fröhlich, M., Hutter, B., et al. (2018) · ESMO Open · doi:10.1136/esmoopen-2018-eacr25.426 · Cited by 21 · see citing works
Detection of infectious Bovine polyomavirus
Nairn, C., Lovatt, A., & Galbraith, D. N. (2003) · Biologicals · doi:10.1016/j.biologicals.2003.08.005 · Cited by 10 · see citing works
GFusion: an Effective Algorithm to Identify Fusion Genes from Cancer RNA-Seq Data
Zhao, J., Chen, Q., Wu, J., Han, P., & Song, X. (2017) · Scientific Reports · doi:10.1038/s41598-017-07070-6 · Cited by 10 · see citing works
Zhao, J., Li, X., Yao, Q., Li, M., Zhang, J., Ai, B., Liu, W., Wang, Q., Feng, C., Liu, Y., et al. (2016) · Oncotarget · doi:10.18632/oncotarget.11064 · Cited by 7 · see citing works
Paciello, G., & Ficarra, E. (2017) · BMC Bioinformatics · doi:10.1186/s12859-016-1450-6 · Cited by 6 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
Proteogenomic and metabolomic characterization of human glioblastoma
Wang, L.-B., Karpova, A., Gritsenko, M. A., Kyle, J. E., Cao, S., Li, Y., Rykunov, D., Colaprico, A., Rothstein, J. H., Hong, R., et al. (2021) · Cancer Cell · doi:10.1016/j.ccell.2021.01.006 · Cited by 661 · see citing works
Accurate and efficient detection of gene fusions from RNA sequencing data
Uhrig, S., Ellermann, J., Walther, T., Burkhardt, P., Fröhlich, M., Hutter, B., Toprak, U. H., Neumann, O., Stenzinger, A., Scholl, C., et al. (2021) · Genome Research · doi:10.1101/gr.257246.119 · Cited by 526 · see citing works
Biologically informed deep neural network for prostate cancer discovery
Elmarakeby, H. A., Hwang, J., Arafeh, R., Crowdis, J., Gang, S., Liu, D., AlDubayan, S. H., Salari, K., Kregel, S., Richter, C., et al. (2021) · Nature · doi:10.1038/s41586-021-03922-4 · Cited by 456 · see citing works
An Organoid Biobank of Neuroendocrine Neoplasms Enables Genotype-Phenotype Mapping
Kawasaki, K., Toshimitsu, K., Matano, M., Fujita, M., Fujii, M., Togasaki, K., Ebisudani, T., Shimokawa, M., Takano, A., Takahashi, S., et al. (2020) · Cell · doi:10.1016/j.cell.2020.10.023 · Cited by 238 · see citing works
A first-generation pediatric cancer dependency map
Dharia, N. V., Kugener, G., Guenther, L. M., Malone, C. F., Durbin, A. D., Hong, A. L., Howard, T. P., Bandopadhayay, P., Wechsler, C. S., Fung, I., et al. (2021) · Nature Genetics · doi:10.1038/s41588-021-00819-w · Cited by 153 · see citing works
Dileep, V., Boix, C. A., Mathys, H., Marco, A., Welch, G. M., Meharena, H. S., Loon, A., Jeloka, R., Peng, Z., Bennett, D. A., et al. (2023) · Cell · doi:10.1016/j.cell.2023.08.038 · Cited by 130 · see citing works
ChimerDB 4.0: an updated and expanded database of fusion genes
Jang, Y. E., Jang, I., Kim, S., Cho, S., Kim, D., Kim, K., Kim, J., Hwang, J., Kim, S., Kim, J., et al. (2019) · Nucleic Acids Research · doi:10.1093/nar/gkz1013 · Cited by 108 · see citing works
Drug screening at single-organoid resolution via bioprinting and interferometry
Tebon, P. J., Wang, B., Markowitz, A. L., Davarifar, A., Krawczuk, P., Murray, G., Nguyen, H. T. L., Tavanaie, N., Nguyen, T. L., Boutros, P. C., et al. (2021) · doi:10.1101/2021.10.03.462896 · Cited by 155 · see citing works
- Authors
- Haas, B. J., Dobin, A., Li, B., Stransky, N., Pochet, N., & Regev, A.
- Affiliations
- Broad Institute (US)
- Cold Spring Harbor Laboratory (US)
- Celsius Therapeutics (United States) (US)
- Corresponding author
- Haas, Brian J.
- Venue
- Genome biology
- Published
- 2019-10-21
- Volume
- 20
- Issue
- 1
- Pages
- 213-213
- ISSN
- 1465-6906 (ISSN-L)
- 1474-760X
- PMC
- PMC6802306
- OpenAlex
- W2980759299
- Cited by
- 646
- References
- 76
- Citations by year
- 2026: 70 · 2025: 108 · 2024: 93 · 2023: 101 · 2022: 91 · 2021: 132 · 2020: 46 · 2019: 4
- FWCI
- 22.54
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- Genome biology (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Cold Spring Harbor Laboratory Institutional Repository (Cold Spring Harbor Laboratory) (acceptedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- DSpace@MIT (Massachusetts Institute of Technology) (submittedVersion, cc-by)
- Funders
- National Cancer Institute (U24CA180922, R50CA211461, R21CA209940, U01CA214846)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › RNA Research and Splicing
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Cancer Research › Cancer Genomics and Diagnostics
- Keywords
- fusion transcript detection, RNA-seq, read mapping, de novo assembly, STAR-Fusion, Arriba, benchmarking, tumor transcriptome, oncogenic viruses, method accuracy
- MeSH terms
- Neoplasms, Software, Sequence Analysis, RNA, Benchmarking, Genomics, Gene Fusion, Transcriptome
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
